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About us

Karlshochschule combines business, society, and culture to create an international and practice-oriented study program.

Contact

  • Karlstraße 36 – 38, 76133 Karlsruhe, DE
  • +49 721 48095 0
  • info@karlshochschule.de
  • Mo. – Fr. 8:30 – 17:00 Uhr

Prof. Dr. Sasanka Potluri

Professor of General Computer Science and Medical Informatics

Sasanka works on AI that has to survive contact with a Tuesday afternoon. Not a benchmark, not a demo — a hospital where the platelets expire, the transport team is short-staffed and someone is waiting on a bed. He spent years teaching neural networks to spot attacks on industrial control systems before turning the same question toward healthcare: what does it take to make a model useful to people who cannot pause their work to accommodate it?

From the factory floor to the hospital ward

Sasanka’s doctoral work sat at an unglamorous but critical intersection: deep learning applied to intrusion detection in industrial control systems, including the detection of false data injection attacks on the networks that run physical infrastructure. From there he moved into biomedical engineering — machine learning for gait segmentation and abnormality detection using wearable sensor platforms — and then to healthcare operations, most recently leading the KI-LoV junior research group at University Hospital Jena. Three fields, one consistent question: how do you make a learning system trustworthy when something real depends on the output?

Optimisation is a patient problem

His current research is unusually concrete. Route planning for moving patients between hospital departments. A data-driven model for managing platelet inventory so fewer units are wasted. Discrete event simulation to find where intra-hospital transport actually breaks down. This is the part of health IT that rarely makes headlines and determines whether a hospital works. Students in his modules learn to formulate problems like these properly before reaching for a model — because the hard part is almost never the algorithm.

The problems ahead of the data

Alongside the optimisation work, Sasanka researches the generation of synthetic health data — a response to a real bind, where the datasets needed to build good clinical tools are also the datasets that cannot simply be shared. He also works on digital health equity, asking who is served and who is missed when care is mediated by systems. Generative AI runs through both. It is a research agenda that treats ethics as an engineering constraint rather than an afterthought.

Building the Computer Science programme

Sasanka joined Karlshochschule in September 2025 and heads the Computer Science programme. He teaches machine learning, deep learning, generative AI, AI algorithms, IT security and distributed systems, and supervises BSc, MSc and PhD projects across medical informatics, clinical decision support and health logistics. His courses are not a tour of the field. They ask students to build something and then find out where it fails.

The algorithm is rarely the hard part. Getting the problem right is.

Facts, figures and the full CV

  • Head of the Computer Science Program
  • At the university since September 2025
  • Artificial Intelligence
  • Machine Learning and Deep Learning
  • Generative AI
  • Biomedical Statistics
  • Digital Signal Processing
  • Clinical Decision Support Systems
  • Data Science
  • Introduction to Medical Informatics
  • Machine Learning
  • AI Algorithms
  • Neural Networks and Deep Learning
  • IT Security
  • Distributed Systems

Sasanka Potluri supervises research projects and theses (BSc, MSc and PhD level) in:

  • Medical Informatics
  • AI and its applications
  • Generative AI
  • Clinical Decision Support Systems
  • Health Logistics
  • Resource and process optimization in hospitals
  • Research on generating synthetic health data
  • Studies in digital health equity
  • Generative AI in healthcare
  • Dr.-Ing. in Electrical Engineering & Information Technology, Otto von Guericke University Magdeburg, Germany
  • Dipl.-Ing. in Information Technology, Alpen-Adria University Klagenfurt, Austria
  • B.Tech in Electronics & Communication Engineering, Jawaharlal Nehru Technological University, Kakinada, India
  • Junior Research Group Leader, “KI-LoV”, University Hospital Jena, Germany
  • Project Leader, Faculty of Human Sciences, Otto von Guericke University Magdeburg
  • Research Scientist, Faculty of Electrical Engineering & Information Technology, Otto von Guericke University Magdeburg
  • Research & Project Assistant for EU project, Faculty of Computer Science, Otto von Guericke University Magdeburg
  • Since 2024 — Member and reviewer, GMDS (German Society for Medical Informatics, Biometry and Epidemiology)
  • Since 2024 — Reviewer, European Federation for Medical Informatics
  • Since 2020 — Reviewer, IEEE Transactions on Network and Service Management
  • Since 2017 — Reviewer, Elsevier journals including Engineering Applications of Artificial Intelligence and Journal of King Saud University – Computer & Information Sciences

Healthcare and biomedical informatics

  • Zhu, Y., Spreckelsen, C., Schilling, M. & Potluri, S. (2025). Intelligent blood product management in hospital: A data-driven model for optimizing platelet inventory. International Conference on AI in Healthcare (AIiH).
  • Karthikeyan, S. & Potluri, S. (2024). Route planning for intra-hospital patient transportation using metaheuristics and mixed integer linear programming. 34th Medical Informatics Europe Conference (MIE).
  • Sarshar, M., Potluri, S. & Schega, L. (2021). Gait phase estimation by using LSTM in IMU-based gait analysis – proof of concept. Sensors, MDPI.
  • Potluri, S., Chandran, A., Diedrich, C. & Schega, L. (2019). Machine learning based human gait segmentation with wearable sensor platform. 41st IEEE EMBC.
  • Potluri, S., Ravuri, S., Diedrich, C. & Schega, L. (2019). Deep learning based gait abnormality detection using wearable sensor system. 41st IEEE EMBC.

Industrial systems security and machine learning

  • Potluri, S., Ahmed, S. & Diedrich, C. (2020). Securing industrial control systems from false data injection attacks with convolutional neural networks. In Development and Analysis of Deep Learning Architectures, ch. 8. Springer.
  • Potluri, S. & Diedrich, C. (2019). Deep learning based efficient anomaly detection for securing process control systems against injection attacks. 15th IEEE CASE.
  • Potluri, S., Diedrich, C., Nanduru, S. R. R. & Vasamshetty, K. (2019). Development of an injection attack toolbox in MATLAB/Simulink for attack simulation in industrial control system applications. 17th IEEE INDIN.
  • Potluri, S., Ahmed, S. & Diedrich, C. (2018). Convolutional neural networks for multi-class intrusion detection system. International Conference on Mining Intelligence and Knowledge Exploration (MIKE).
  • Potluri, S., Sangala, G. K. R. & Diedrich, C. (2017). Identifying false data injection attacks in industrial control systems using artificial neural networks. 22nd IEEE ETFA.
  • Potluri, S., Henry, N. F. & Diedrich, C. (2017). Evaluation of hybrid deep learning techniques for ensuring security in networked control systems. 22nd IEEE ETFA.
  • Potluri, S. & Diedrich, C. (2016). Accelerated deep neural networks for enhanced intrusion detection system. 21st IEEE ETFA.
  • Potluri, S. & Diedrich, C. (2016). Deep feature extraction for multi-class intrusion detection in industrial control systems. 9th ICCSIT.
  • Potluri, S. & Diedrich, C. (2016). High performance intrusion detection and prevention systems: A survey. 15th ECCWS.

Earlier work

  • Dietrich, A., Kaiser, J. & Potluri, S. (2013). Application driven environment representation. 7th UBICOMM.
  • Zug, S., Brade, T., Kaiser, J. & Potluri, S. (2012). An approach supporting fault-propagation analysis for smart sensor systems. SAFECOMP.
  • Potluri, S., Fasih, A., Vutukuru, L. K., Al Machot, F. & Kyamakya, K. (2011). CNN based high performance computing for real-time image processing on GPU. 16th IEEE ISTET.

Industry dialogues

  • Belyaev, A., Sriramula, A. T., Potluri, S. & Diedrich, C. (2019). Machine-as-a-Service: Integration von Blockchain und Konzepten der I4.0. Automation Congress, Baden-Baden.
  • Potluri, S., Schröder, T. & Diedrich, C. (2018). Monitoring und Optimierung in der Fertigungstechnik mit NAMUR Open Architecture. Automation Congress, Baden-Baden.

Research posters

  • Karthikeyan, S., Spreckelsen, C. & Potluri, S. (2025). Discrete event simulation for optimization of intra-hospital patient transportation. 70th GMDS Annual Conference.
  • Potluri, S., Karthikeyan, S. & Zhu, Y. (2024). Intelligent healthcare logistics: Steps towards optimizing resources and processes in hospitals. MII Symposium.
  • Kondragunta, J. & Potluri, S. (2017). Early identification of complex foot problems with adaptive artificial intelligence. 5th BME IDEA Europe.
  • Potluri, S. & Diedrich, C. (2017). Securing industrial control systems with self-organizing maps. Symposium: Digitalisierung in der Automation, Magdeburg.

The full publication list is available on request.

Want to study with Sasanka?

He teaches across the Computer Science programme and supervises projects in medical informatics, AI and health logistics. Come to an info day, sit in on a session, or write to him directly.

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